Senior Machine Learning Engineer (Health Insights)

TL;DR

Senior Machine Learning Engineer (Health Insights): Developing and deploying scalable machine learning systems for health and fitness wearables with an accent on physiological data streams and production-grade reliability. Focus on translating research prototypes into high-performance inference services, optimizing system architecture, and ensuring robust model performance for millions of members.

Location: Must be based in or able to relocate to Boston, MA

Salary: $150,000–$210,000

Company

WHOOP is an advanced health and fitness wearable company dedicated to unlocking human performance through deep physiological insights.

What you will do

• Create and maintain production services for health analysis in collaboration with data scientists and MLOps engineers.
• Collaborate with data engineers to improve ML pipelines, tooling, and validation systems.
• Translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency.
• Work with researchers and product teams to align model development with physiological insights.
• Participate in on-call rotations to ensure service uptime and performance.

Requirements

• Must be based in or able to relocate to Boston, MA.
• Bachelor’s degree in Computer Science, Data Science, or related field.
• 4+ years of professional experience in ML engineering or applied research.
• Strong Python coding skills with a focus on production-quality code.
• Experience deploying and operating ML inference systems at scale on cloud platforms (AWS or GCP).
• Strong fundamentals in backend development, including APIs, reliability, and monitoring.

Nice to have

• Master’s degree in a relevant field.
• 2+ years of experience applying advanced statistical techniques.
• Experience working with time series, wearable, or high-frequency sensor data.

Culture & Benefits

• Competitive base salary with equity package.
• Comprehensive health and wellness benefits.
• Opportunity to work on impactful health technology at scale.
• Inclusive and diverse work environment.